{"product_id":"maximum-entropy-econometrics-isbn-9780471953111","title":"Maximum Entropy Econometrics","description":"In the theory and practice of econometrics the model, the methodand the data are all interdependent links in informationrecovery-estimation and inference. Seldom, however, are theeconomic and statistical models correctly specified, the datacomplete or capable of being replicated, the estimation rulesoptimal and the inferences free of distortion. Faced with theseproblems, Maximum Entropy Economeirics provides a new basis forlearning from economic and statistical models that may benon-regular in the sense that they are ill-posed or underdeterminedand the data are partial or incomplete. By extending the maximumentropy formalisms used in the physical sciences, the authorspresent a new set of generalized entropy techniques designed torecover information about economic systems. The authors compare thegeneralized entropy techniques with the performance of the relevanttraditional methods of information recovery and clearly demonstratetheories with applications including\u003cbr\u003e * Pure inverse problems that include first order Markov processes,and input-output, multisectoral or SAM models to\u003cbr\u003e * Inverse problems with noise that include statistical modelssubject to ill-conditioning, non-normal errors, heteroskedasticity,autocorrelation, censored, multinomial and simultaneous responsedata, as well as model selection and non-stationary and dynamiccontrol problems\u003cbr\u003e Maximum Entropy Econometrics will be of interest to econometricianstrying to devise procedures for recovering information from partialor incomplete data, as well as quantitative economists in financeand business, statisticians, and students and applied researchersin econometrics, engineering and the physical sciences. The Classical Maximum Entropy Formalism: A Review.\u003cbr\u003e \u003cbr\u003e PURE INVERSE PROBLEMS.\u003cbr\u003e \u003cbr\u003e Basic Maximum Entropy Principle: Formulation and Extensions.\u003cbr\u003e \u003cbr\u003e Formulation and Solution of Pure Inverse Problems.\u003cbr\u003e \u003cbr\u003e Generalized Pure Inverse Problems.\u003cbr\u003e \u003cbr\u003e LINEAR INVERSE PROBLEMS WITH NOISE.\u003cbr\u003e \u003cbr\u003e Generalized Maximum Entropy (GME) and Cross-Entropy (GCE)Formulations.\u003cbr\u003e \u003cbr\u003e Finite Sample Extensions of GME-GCE.\u003cbr\u003e \u003cbr\u003e GENERAL LINEAR MODEL APPLICATIONS OF GME-GCE.\u003cbr\u003e \u003cbr\u003e GME-GCE Solutions to Ill-conditioned Problems.\u003cbr\u003e \u003cbr\u003e General Linear Statistical Model with a Non-scalar IdentityCovariance Matrix Statistical Model Selection.\u003cbr\u003e \u003cbr\u003e A SYSTEM OF ECONOMIC STATISTICAL RELATIONS.\u003cbr\u003e \u003cbr\u003e Sets of Linear Statistical Models.\u003cbr\u003e \u003cbr\u003e Simultaneous Equations Statistical Model.\u003cbr\u003e \u003cbr\u003e LINEAR AND NON-LINEAR DYNAMIC SYSTEMS.\u003cbr\u003e \u003cbr\u003e Estimation and Inference of Dynamic Linear Inverse Problems.\u003cbr\u003e \u003cbr\u003e Linear and Non-linear Dynamic Systems with Control.\u003cbr\u003e \u003cbr\u003e DISCRETE CHOICE-CENSORED PROBLEMS.\u003cbr\u003e \u003cbr\u003e Recovering Information from Multinomial Response Data.\u003cbr\u003e \u003cbr\u003e Recovering Information from Censored Response Data.\u003cbr\u003e \u003cbr\u003e COMPUTATIONAL NOTES.\u003cbr\u003e \u003cbr\u003e Computing GME-GCE Solutions.\u003cbr\u003e \u003cbr\u003e Epilogue.\u003cbr\u003e \u003cbr\u003e Selected Reading.\u003cbr\u003e \u003cbr\u003e Index. Amos Golan is a professor of economics and directs the Info-Metrics Institute at American University. He is also an External Professor at the Santa Fe Institute and a Senior Associate at Pembroke College, Oxford. His research is primarily in the interdisciplinary field of info-metrics - the science and practice of information processing, modeling, inference, and problem solving with insufficient information. He has published in economics, econometrics, statistics, mathematics, physics and philosophy journals. His books include Maximum Entropy Econometrics: Robust Estimation with Limited Data (coauthored with Judge and Miller) and Information and Entropy Econometrics - A Review and Synthesis.  In the theory and practice of econometrics the model, the method and the data are all interdependent links in information recovery-estimation and inference. Seldom, however, are the economic and statistical models correctly specified, the data complete or capable of being replicated, the estimation rules ?optimal? and the inferences free of distortion. Faced with these problems, Maximum Entropy Economeirics provides a new basis for learning from economic and statistical models that may be non-regular in the sense that they are ill-posed or underdetermined and the data are partial or incomplete. By extending the maximum entropy formalisms used in the physical sciences, the authors present a new set of generalized entropy techniques designed to recover information about economic systems. The authors compare the generalized entropy techniques with the performance of the relevant traditional methods of information recovery and clearly demonstrate theories with applications including \u003cul\u003e \u003cli\u003ePure inverse problems that include first order Markov processes, and input-output, multisectoral or SAM models to\u003c\/li\u003e \u003cli\u003eInverse problems with noise that include statistical models subject to ill-conditioning, non-normal errors, heteroskedasticity, autocorrelation, censored, multinomial and simultaneous response data, as well as model selection and non-stationary and dynamic control problems\u003c\/li\u003e \u003c\/ul\u003e Maximum Entropy Econometrics will be of interest to econometricians trying to devise procedures for recovering information from partial or incomplete data, as well as quantitative economists in finance and business, statisticians, and students and applied researchers in econometrics, engineering and the physical sciences.","brand":"Wiley","offers":[{"title":"Default Title","offer_id":47989590687973,"sku":"NP9780471953111","price":216.0,"currency_code":"USD","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/1842\/7735\/files\/9780471953111.jpg?v=1761784719","url":"https:\/\/k12savings.com\/es\/products\/maximum-entropy-econometrics-isbn-9780471953111","provider":"K12savings","version":"1.0","type":"link"}